On the Use of Causal Graphical Models for Designing Experiments in the Automotive Domain.
David Issa MattosYuchu LiuPublished in: CoRR (2022)
Keyphrases
- graphical models
- bayesian networks
- belief propagation
- probabilistic model
- random variables
- probabilistic inference
- possibilistic networks
- approximate inference
- probabilistic graphical models
- map inference
- influence diagrams
- models with hidden variables
- factor graphs
- conditional random fields
- conditional independence
- exact inference
- markov networks
- statistical inference
- belief networks
- graph structure
- causal networks
- chain graphs
- conditional probabilities
- causal models
- exponential family
- transfer learning
- higher order